Gokul Prabhakaran

Papers

Total Citations

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About

Gokul Prabhakaran is a rising researcher in robotics and artificial intelligence, with a core focus on enhancing the safety and reliability of bipedal locomotion. His work centers on fall prediction and fault detection for humanoid robots, a critical area for advancing autonomous systems in real-world environments. His most-cited paper, "Fall Prediction for Bipedal Robots: The Standing Phase" (2024), introduces a novel approach using a 1D convolutional neural network (CNN) to detect potential falls caused by abrupt, incipient, and intermittent faults. This method is designed to maximize lead time for fall prevention, significantly improving robot stability and operational safety. With 8 citations already, this work is gaining traction in the robotics community for its practical implications in fault-tolerant control. Prabhakaran’s contributions are particularly notable for addressing the challenging "standing phase," a foundational yet underexplored aspect of bipedal robotics. His research bridges machine learning and mechanical systems, offering scalable solutions for real-time fault detection. As a young scholar, his work promises to shape future developments in autonomous robotics, making him a key figure to watch in the field.